Testing a scaling relation between coherent radio emission and physical parameters of hot magnetic stars
Bibliographic record
Abstract
ABSTRACT Coherent radio emission via electron cyclotron maser emission (ECME) from hot magnetic stars was discovered more than two decades ago, but the physical conditions that make the generation of ECME favourable remain uncertain. Only recently was an empirical relation, connecting ECME luminosity with the stellar magnetic field and temperature, proposed to explain what makes a hot magnetic star capable of producing ECME. This relation was, however, obtained with just 14 stars. Therefore, it is important to examine whether this relation is robust. With the aim of testing the robustness, we conducted radio observations of five hot magnetic stars. This led to the discovery of three more stars producing ECME. We find that the proposed scaling relation remains valid after the addition of the newly discovered stars. However, we discovered that the magnetic field and effective temperature correlate for Teff ≲ 16 kK (likely an artefact of the small sample size), rendering the proposed connection between ECME luminosity and Teff unreliable. By examining the empirical relation in light of the scaling law for incoherent radio emission, we arrive at the conclusion that both types of emission are powered by the same magnetospheric phenomenon. Like the incoherent emission, coherent radio emission is indifferent to Teff for late-B and A-type stars, but Teff appears to become important for early-B type stars, possibly due to higher absorption, or higher plasma density at the emission sites suppressing the production of the emission.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".